1
|
Dai S, Yang Y, Wang D. Chinese Visceral Adiposity Index Predict Prehypertension Progression and Regression: A Prospective Cohort Study Involving Middle-Aged and Older Adults. Am J Hypertens 2024; 37:588-596. [PMID: 38597145 DOI: 10.1093/ajh/hpae041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/18/2024] [Accepted: 04/04/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Limited data are published on the relationship of the Chinese visceral adiposity index (CVAI) with prehypertension progression or regression. Therefore, we investigated this association through the China Health and Retirement Longitudinal Study. METHODS Participants with prehypertension were assigned to two groups according to baseline CVAI, and after 4 years of follow-up, their blood pressure was analyzed for deterioration or improvement. We constructed logistic regression models for assessing the association of CVAI with the progression or regression of prehypertension. A restricted cubic spline (RCS) model was utilized for determining the dose-response association. Subgroup analysis and sensitivity analysis were also conducted. RESULTS The study included 2,057 participants with prehypertension. During the follow-up, 695 participants progressed to hypertension, 561 participants regressed to normotension, and 801 participants remained as prehypertensive. An association was observed between a high CVAI value and a higher incidence of progression to hypertension and between a high CVAI value and a lower incidence of regression to normotension (OR = 1.66 and 0.58, 95% CI: 1.35-2.05 and 0.47-0.73, respectively). The RCS model exhibited a linear association between CVAI and prehypertension progression and regression (all P for non-linear > 0.05). The results of the subgroup and sensitivity analyses agreed with those of the primary analysis. CONCLUSIONS A significant association was noted between CVAI and prehypertension progression and regression. Thus, as part of the hypertension prevention strategy, monitoring CVAI is crucial in individuals with prehypertension.
Collapse
Affiliation(s)
- Senjie Dai
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yang Yang
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Dongying Wang
- The First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| |
Collapse
|
2
|
Wang Y, Zhang X, Li Y, Gui J, Mei Y, Yang X, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Obesity- and lipid-related indices as a predictor of type 2 diabetes in a national cohort study. Front Endocrinol (Lausanne) 2024; 14:1331739. [PMID: 38356678 PMCID: PMC10864443 DOI: 10.3389/fendo.2023.1331739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/26/2023] [Indexed: 02/16/2024] Open
Abstract
Objective Type 2 diabetes mellitus (T2DM) remains a major and widespread public health concern throughout the world. The prevalence of T2DM in the elderly has risen to the top of the list of public health concerns. In this study, obesity- and lipid-related indices were used to predict T2DM in middle-aged and elderly Chinese adults. Methods The data came from the China Health and Retirement Longitudinal Study (CHARLS), including 7902 middle-aged and elderly participants aged 45 years or above. The study assessed the association of obesity- and lipid-related indices and T2DM by measuring 13 indicators, including body mass index (BMI), waist circumference(WC), waist-height ratio (WHtR), conicity index(CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The association of 13 obesity- and lipid-related indices with T2DM was investigated by binary logistic regression. Additionally, the predictive anthropometric index was evaluated, and the ideal cut-off value was established using the receiver operating characteristic (ROC) curve analysis and area under the curve (AUC). Results The study included 7902 participants, of whom 3638(46.04) and 4264(53.96) were male and female. The prevalence of T2DM in mid-aged and old adults in China was 9.02% in males and 9.15% in females. All the above 13 indicators show a modest predictive power (AUC>0.5), which was significant for predicting T2DM in adults (middle-aged and elderly people) in China (P<0.05). The results revealed that TyG-WHtR [AUC =0.600, 95%CI: 0.566-0.634] in males and in females [AUC =0.664, 95%CI: 0.636-0.691] was the best predictor of T2DM (P<0.05). Conclusion Most obesity- and lipid-related indices have important value in predicting T2DM. Our results can provide measures for the early identification of T2DM in mid-aged and elderly Chinese to reduce the prevalence of T2DM and improve health.
Collapse
Affiliation(s)
- Ying Wang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Xiaoyun Zhang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Yujin Mei
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Xue Yang
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, Wuhu, An Hui, China
| | - Lei-lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, Linghe District, Jinzhou, Liaoning, China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wanna Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu, An Hui, China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| |
Collapse
|